Text-to-Speech
Transformers
ONNX
English
bitsandbytes
llama
text-generation-inference
trl
tts
onnxruntime-genai
Instructions to use Prince-1/OrpheusTTS-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prince-1/OrpheusTTS-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Prince-1/OrpheusTTS-ONNX")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prince-1/OrpheusTTS-ONNX", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72c94d26d1755ec8b7a9f9e84a797070cdd0a6c394fe5379aa6a9013a9642f80
- Size of remote file:
- 22.8 MB
- SHA256:
- fc3fecb199b4170636dbfab986d25f628157268d37b861f9cadaca60b1353bce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.